
CohortMethod is part of the
OHDSI Methods Library
s
New-user cohort studies using
large-scale regression for
propensity and outcome
models
Cohort Method
s
Self-Controlled Case Series
analysis using few or many
predictors, includes splines for
age and seasonality.
Self-Controlled Case Series
s
A self-controlled cohort
design, where time preceding
exposure is used as control.
Self-Controlled Cohort
s
A self-controlled design, but
using temporal patterns
around other exposures and
outcomes to correct for time-
varying confounding.
IC Temporal Pattern Disc.
s
Build and evaluate predictive
models for user-specified
outcomes, using a wide array
of machine learning
algorithms.
Patient Level Prediction
s
Use negative control
exposure-outcome pairs to
profile and calibrate a
particular analysis design.
Empirical Calibration
s
Use real data and established
reference sets as well as
simulations injected in real
data to evaluate the
performance of methods.
Method Evaluation
s
Connect directly to a wide
range of database platforms,
including SQL Server, Oracle,
and PostgreSQL.
Database Connector
s
Generate SQL on the fly for
the various SQL dialects.
Sql Render
s
Highly efficient
implementation of regularized
logistic, Poisson and Cox
regression.
Cyclops
s
Support tools that didn’t fit
other categories, including
tools for maintaining R
libraries.
Ohdsi R Tools
Estimation methods Prediction methods Method characterization Supporting packages
Under construction
s
Automatically extract large
sets of features for user-
specified cohorts using data in
the CDM.
Feature Extraction
s
Case-control studies,
matching controls on age,
gender, provider, and visit
date. Allows nesting of the
study in another cohort.
Case-control